MOGRIFY® PLATFORM
Systematically predict the transcriptomic switches required
to produce any target cell type from any source cell type.
The MOGRIFY® technology was developed as a systematic means of identifying the key regulatory switches, such as an optimal combination of transcription factors, required to drive cell identity. The platform can be used to enhance existing stem-cell forward reprogramming methods or can bypass development pathways altogether, affecting a direct trans-differentiation between a mature cell type to another mature cell type.
The platform follows a step-wise scientific approach to driving cell identity. Firstly, the RNA of the source and target cell types is sequenced in order to compare the gene expression levels in the context of all other possible cell types. Simultaneously, local transcriptomic regulatory networks are built around each regulatory gene in the human genome to calculate and rank the effect of the genes on the desired cell conversion by querying large-scale regulatory networks. The optimal combination of key regulators is predicted to maximize network coverage while avoiding redundancies. Once this optimal combination has been identified, the DNA sequence of each regulatory gene is encoded into delivery vectors, which are transduced into the source cell type causing changes in DNA expression profile and therefore switching the genetic programs of the cell which induces the conversion between source and target cell type.
In addition to identifying transcription factor-driven cell conversions, small molecules that are able to affect the expression of the key predicted transcription factors can be identified to create a small molecule conversion cocktail. This approach has the added benefit of not requiring the transduction of transcription factors and consequently holds greater potential as an in vivo reprogramming therapy.
Step 1 Calculation of contextual gene expression
Step 2 Identification and scoring of genes that require change from source to target cell
Step 3 Building local regulatory network of influence around each transcription factor (TF)
Step 4 Scoring of the conversion potential of each TF and optimization of network coverage with combinations of TFs
Over 150 cell types, of which 32 cell conversions (13 successfully validated in vitro) are covered in the foundational patent. Images adapted from Rackham OJL et al. A predictive computational framework for direct reprogramming between human cell types. Nature Genetics (2016).
Applying Mogrify and EpiMogrify
To ENHANCE
Efficacy
- Enhances existing stem-cell forward reprogramming methods.
- Bypasses development pathways altogether, affecting direct transdifferentiation between a mature cell type to another.
Safety
- Produces mature cells to avoid the tumorigenicity- and immunogenicity-associated characteristics of pluripotent stem cells.
- Queries FANTOM5 and other proprietary data sources to improve prediction quality, prediction accuracy and cell conversion efficacy.
Scalability
- Produces any target cell type from any source cell type.
- Identifies the optimal culture conditions required to maintain and support the conversion of cells in chemically defined media.
- Capacity to identify small molecules known to affect the expression of the key Mogrify predicted transcription factors, avoiding the need for their transduction, and offering greater potential as an in vivo reprogramming therapy.
Our
PIPELINE
| AREA | Sample Acquisition | Bioinformatics | In vitro PoC | In vivo PoC | IND | Clinical | Marketing |
|---|---|---|---|---|---|---|---|
| Ophthalmology | mogrify | mogrify | mogrify | partner | partner | ||
| Immunology (& hematology) |
mogrify | mogrify | mogrify | mogrify | partner | partner | |
| Collaborations (Pancreatic, Lung, Immune & Others) |
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| mogrify | Mogrify Progress | partner | Expect to Partner |
Featured
RESOURCES
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This review published in Cell & Gene Therapy Insights discusses the current challenges for autologous and allogeneic adoptive cellular therapies (ACT) and how big dataset analysis is opening paths to overcome resistance and enhance the efficacy of ACT.